Utilização de modelos matemáticos/estocásticos na avaliação da ocorrência de dengue em função do clima na Paraíba.

Abstract

The climate has a direct influence on certain morbidities, which is the study object of several multidisciplinary research areas. In order to evaluate its effects on humans, this task is the area of Human Biometeorology. This paper presents an approach to use different observation techniques for the risk of dengue outbreak, together with a research proposal for the State of Paraiba. Such techniques are formed by a dynamic modeling of the Institute de Recherché Pour le Développement - IRD (mIRD), the model Seasonal Auto Regressive Integrated Moving Average (SARIMA), model Holt - Winters and Neural Networks (RNA). The data used in this study were reported cases of dengue fever by the Health Department of the State of Paraíba, as well as data of meteorological variables from the National Institute of Meteorology (INMET). The results of the proposed techniques show that the model mIRD observes the characteristic entomological values if the insect distinguished regarding the studied localizations, giving a risk index directly dependent on the rate of reproduction of the insect, while the other models make a prediction taking into account the number of reported cases (Holt and SARIMA-WINTRS), using also meteorological variables (RNA), where we obtained a good agreement between observed and predicted data.